Human Motion Tracking by Registering an Articulated Surface to 3-D Points and Normals

Radu Horaud 1 Matti Niskanen 1 Guillaume Dewaele 2 Edmond Boyer 1
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : We address the problem of human motion tracking by registering a surface to 3-D data. We propose a method that iteratively computes two things: Maximum likelihood estimates for both the kinematic and free-motion parameters of a kinematic human-body representation, as well as probabilities that the data are assigned either to a body part, or to an outlier cluster. We introduce a new metric between observed points and normals on one side, and a parameterized surface on the other side, the latter being defined as a blending over a set of ellipsoids. We claim that this metric is well suited when one deals with either visual-hull or visual-shape observations. We illustrate the method by tracking human motions using sparse visual-shape data (3-D surface points and normals) gathered from imperfect silhouettes.
Type de document :
Article dans une revue
IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2009, 31 (1), pp.158-163. 〈10.1109/TPAMI.2008.108〉
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Contributeur : Radu Horaud <>
Soumis le : mercredi 13 janvier 2010 - 16:05:17
Dernière modification le : dimanche 14 septembre 2014 - 23:25:30
Document(s) archivé(s) le : jeudi 17 juin 2010 - 22:44:09

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Radu Horaud, Matti Niskanen, Guillaume Dewaele, Edmond Boyer. Human Motion Tracking by Registering an Articulated Surface to 3-D Points and Normals. IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2009, 31 (1), pp.158-163. 〈10.1109/TPAMI.2008.108〉. 〈inria-00446898〉

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